Dark Sky to Superset

This page provides you with instructions on how to extract data from Dark Sky and analyze it in Superset. (If the mechanics of extracting data from Dark Sky seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Dark Sky?

Dark Sky Company specializes in weather forecasting and visualization. Its software powers the company's own Dark Sky weather app, and its API provides current, historical, and forecast data to other apps.

Getting data out of Dark Sky

Dark Sky provides an API that lets developers retrieve data stored in the platform about temperature, precipitation, wind, and other meteorological conditions, using the format https://api.darksky.net/forecast/[key]/[latitude],[longitude],[time]?parameter=value1,value2. For example, to retrieve information about Boston weather, you could call GET https://api.darksky.net/forecast/key/42.3601,-71.0589.

Sample Dark Sky data

Here's an example of the kind of response you might see with a query like the one above.

{
          "latitude": 42.3601,
          "longitude": -71.0589,
          "timezone": "America/New_York",
          "currently": {
              "time": 1509993277,
              "summary": "Drizzle",
              "icon": "rain",
              "nearestStormDistance": 0,
              "precipIntensity": 0.0089,
              "precipIntensityError": 0.0046,
              "precipProbability": 0.9,
              "precipType": "rain",
              "temperature": 66.1,
              "apparentTemperature": 66.31,
              "dewPoint": 60.77,
              "humidity": 0.83,
              "pressure": 1010.34,
              "windSpeed": 5.59,
              "windGust": 12.03,
              "windBearing": 246,
              "cloudCover": 0.7,
              "uvIndex": 1,
              "visibility": 9.84,
              "ozone": 267.44
          },
          "minutely": {
              "summary": "Light rain stopping in 13 min., starting again 30 min. later.",
              "icon": "rain",
              "data": [{
                  "time": 1509993240,
                  "precipIntensity": 0.007,
                  "precipIntensityError": 0.004,
                  "precipProbability": 0.84,
                  "precipType": "rain"
              },
            ...
            ]
          },
          "hourly": {
              "summary": "Rain starting later this afternoon, continuing until this evening.",
              "icon": "rain",
              "data": [{
                  "time": 1509991200,
                  "summary": "Mostly Cloudy",
                  "icon": "partly-cloudy-day",
                  "precipIntensity": 0.0007,
                  "precipProbability": 0.1,
                  "precipType": "rain",
                  "temperature": 65.76,
                  "apparentTemperature": 66.01,
                  "dewPoint": 60.99,
                  "humidity": 0.85,
                  "pressure": 1010.57,
                  "windSpeed": 4.23,
                  "windGust": 9.52,
                  "windBearing": 230,
                  "cloudCover": 0.62,
                  "uvIndex": 1,
                  "visibility": 9.32,
                  "ozone": 268.95
              },
            ...
            ]
          },
         "daily": {
              "summary": "Mixed precipitation throughout the week, with temperatures falling to 39°F on Saturday.",
              "icon": "rain",
              "data": [{
                  "time": 1509944400,
                  "summary": "Rain starting in the afternoon, continuing until evening.",
                  "icon": "rain",
                  "sunriseTime": 1509967519,
                  "sunsetTime": 1510003982,
                  "moonPhase": 0.59,
                  "precipIntensity": 0.0088,
                  "precipIntensityMax": 0.0725,
                  "precipIntensityMaxTime": 1510002000,
                  "precipProbability": 0.73,
                  "precipType": "rain",
                  "temperatureHigh": 66.35,
                  "temperatureHighTime": 1509994800,
                  "temperatureLow": 41.28,
                  "temperatureLowTime": 1510056000,
                  "apparentTemperatureHigh": 66.53,
                  "apparentTemperatureHighTime": 1509994800,
                  "apparentTemperatureLow": 35.74,
                  "apparentTemperatureLowTime": 1510056000,
                  "dewPoint": 57.66,
                  "humidity": 0.86,
                  "pressure": 1012.93,
                  "windSpeed": 3.22,
                  "windGust": 26.32,
                  "windGustTime": 1510023600,
                  "windBearing": 270,
                  "cloudCover": 0.8,
                  "uvIndex": 2,
                  "uvIndexTime": 1509987600,
                  "visibility": 10,
                  "ozone": 269.45,
                  "temperatureMin": 52.08,
                  "temperatureMinTime": 1510027200,
                  "temperatureMax": 66.35,
                  "temperatureMaxTime": 1509994800,
                  "apparentTemperatureMin": 52.08,
                  "apparentTemperatureMinTime": 1510027200,
                  "apparentTemperatureMax": 66.53,
                  "apparentTemperatureMaxTime": 1509994800
              },
            ...
            ]
          },
          "alerts": [
          {
            "title": "Flood Watch for Mason, WA",
            "time": 1509993360,
            "expires": 1510036680,
            "description": "...FLOOD WATCH REMAINS IN EFFECT THROUGH LATE MONDAY NIGHT...\nTHE FLOOD WATCH CONTINUES FOR\n* A PORTION OF NORTHWEST WASHINGTON...INCLUDING THE FOLLOWING\nCOUNTY...MASON.\n* THROUGH LATE FRIDAY NIGHT\n* A STRONG WARM FRONT WILL BRING HEAVY RAIN TO THE OLYMPICS\nTONIGHT THROUGH THURSDAY NIGHT. THE HEAVY RAIN WILL PUSH THE\nSKOKOMISH RIVER ABOVE FLOOD STAGE TODAY...AND MAJOR FLOODING IS\nPOSSIBLE.\n* A FLOOD WARNING IS IN EFFECT FOR THE SKOKOMISH RIVER. THE FLOOD\nWATCH REMAINS IN EFFECT FOR MASON COUNTY FOR THE POSSIBILITY OF\nAREAL FLOODING ASSOCIATED WITH A MAJOR FLOOD.\n",
            "uri": "http://alerts.weather.gov/cap/wwacapget.php?x=WA1255E4DB8494.FloodWatch.1255E4DCE35CWA.SEWFFASEW.38e78ec64613478bb70fc6ed9c87f6e6"
          },
          ...
          ],
          {
            "flags": {
              "units": "us",
              ...
            }
          }

Preparing Dark Sky data

If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. Dark Sky's documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.

Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. In these cases you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

Keeping Dark Sky data up to date

At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, Dark Sky's API results include fields like time that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've taken new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Dark Sky to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Dark Sky data in Superset is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Dark Sky to Redshift, Dark Sky to BigQuery, Dark Sky to Azure SQL Data Warehouse, Dark Sky to PostgreSQL, Dark Sky to Panoply, and Dark Sky to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Dark Sky with Superset. With just a few clicks, Stitch starts extracting your Dark Sky data via the API, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Superset.